Prediction of turbine gas Meter error in high-pressure by CFD techniques: A novel approach to reduce high-pressure calibration (HPC) costs

Abstract

Calibrating gas meters to their operating conditions are ideal for defining accuracy, but obstacles like economics, time, physical limitations, and a lack of high-pressure calibration facilities often prevent this. A Computational Fluid Dynamics (CFD) model was created using the motion equations simultaneously angular momentum balance in steady state and the standard k-ε turbulence model to improve the prediction of Turbine Gas Meter (TGM) performance at both high-pressure and atmospheric conditions. Utilizing the Multiple Reference Frame (MRF) model, numerical simulations for a 2-inch turbine gas meter (DN 50, G65, and PN/ANSI 150) were conducted, and the proposed model's accuracy was validated by comparing atmospheric calibration simulation results with experimental data, demonstrating a Weighted Mean Error (WME) of −0.162%. According to the performance analysis results, the accuracy of the turbine gas meter deteriorated as pressure increased, and the rotor's maximum rise in angular velocity increased by 12% compared to atmospheric pressure. Additionally, it was discovered that pressure variations had a more significant impact on angular velocity at lower flow rates. Also, it was found that pressure has a considerable effect on gas turbine meter performance up to 50 bar (Re = 2.5 × 106). Angular velocity variations are negligible at more tremendous pressures and can be disregarded. Finally, a correlation for turbine gas meter was developed, which can be used to forecast angular velocity at various pressures and the error percentage compared to atmospheric conditions.